Field of the Invention
The present invention relates to the fields of dermoscopy and software for the practice thereof on handheld biomedical screening devices. Specifically, the present invention provides a library of image processing and texture analysis algorithms that run on embedded devices for screening lesions and for plant diseases.
Description of the Related Art
The American Cancer Society predicts that there will be approximately 68,130 new cases of melanoma and 8,700 deaths because of melanoma in U.S. in 2010 (1). Thus, detection of an early melanoma is of paramount importance for successful skin cancer screening. The use of dermoscopy, an imaging technique to visualize structures inside pigmented skin lesions beyond the naked eye, and computerized systems for automated classification of dermoscopic images (2) can drastically improve the diagnostic accuracy of early melanoma. Image classification using interest points has shown success in previous studies (3).
In recent years, cellular phones have made the transition from simple dedicated telephony devices to being small, portable computers with the capability to perform complex, memory- and processor-intensive operations. These new smart devices, generally referred to as smartphones, provide the user with a wide array of communication and entertainment options that until recently required many independent devices. Given advances in medical imaging, smartphones provide an attractive vehicle for delivering image-based diagnostic services at a low cost.
As such, the new generation of smart handheld devices with sophisticated hardware and operating systems has provided a portable platform for running medical diagnostic software, such as the heart rate monitoring (4), diabetes monitoring (5), and experience sampling (6) applications, which combine the usefulness of medical diagnosis with the convenience of a handheld device. Their light operating systems, such as the Apple® iOS® and Google® Android®, the support for user friendly touch gestures, the availability of an SDK for fast application development, the rapid and regular improvements in hardware, and the availability of fast wireless networking over Wi-Fi and 3G make these devices ideal for medical applications.
Thus, there is a recognized need in the art for algorithms for improved detection, analysis and classification of skin lesions that can run on devices with limited memory and computational speed. More specifically, the prior art is deficient in image sampling, processing and texture analysis methods, algorithms and plug-in features, for detection and diagnosis of skin and ocular diseases and plant diseases, that are configured to operate on smart handheld devices. The present invention fulfills this long-standing need and desire in the art.